large-scale multi-user multiple-inputmultiple-output (MU-MIMO) systems and cloud radio access networks (C-RANs) are promising technologies for the fifth generation (5G) of wireless networks. In this context, the use ...
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large-scale multi-user multiple-inputmultiple-output (MU-MIMO) systems and cloud radio access networks (C-RANs) are promising technologies for the fifth generation (5G) of wireless networks. In this context, the use of low-resolution analogue-to-digital converters (ADCs) is key for energy efficiency and for complying with constrained fronthaul links. Processing signals with a few bits implies performance loss and, therefore, techniques that can compensate for quantisation distortion are fundamental. In wireless systems, an automatic gain control (AGC) precedes the ADCs to adjust the input signal level in order to reduce the impact of quantisation. In this work, the authors propose the joint optimisation of the AGC, which works in the remote radio heads (RRHs), and a low-resolution aware (LRA) linear receive filter based on the minimum mean square error (MMSE), which works in the cloud unit (CU), for large-scale MU-MIMO systems with coarsely quantised signals. They develop linear and successive interference cancellation receivers based on the proposed joint AGC and LRA MMSE (AGC-LRA-MMSE) approach. An analysis of the achievable sum rates along with a computational complexity study is also carried out. Simulations show that the proposed AGC-LRA-MMSE design obtains substantial gains in bit error rates and achievable information rates over existing techniques.
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